Paper
Janus-Faced Technological Progress and the Arms Race in the Education of Humans and Chatbots
Authors
Wolfgang Kuhle
Abstract
We study the conditions under which technological advances, in combination with a lognormal wage distribution, incentivize agents into an inefficient educational arms race. Our model emphasizes that lognormal wage distributions imply that agents' wages increase exponentially in the level of their skill as well as in the level of technology. In turn, this exponential relation between skills, technology, and wages pressures agents into an exhausting race for the tails of the economy's skill distribution. Moreover, technological advances and overinvestment in education increase GDP and inequality, while welfare may decline. In an alternative interpretation, our model studies firms that invest in artificial intelligence of their chatbots and AI agents. For a wide range of specifications, firms, just like humans, have an incentive to choose corner solutions where investment is limited only by borrowing constraints.
Metadata
Related papers
Vibe Coding XR: Accelerating AI + XR Prototyping with XR Blocks and Gemini
Ruofei Du, Benjamin Hersh, David Li, Nels Numan, Xun Qian, Yanhe Chen, Zhongy... • 2026-03-25
Comparing Developer and LLM Biases in Code Evaluation
Aditya Mittal, Ryan Shar, Zichu Wu, Shyam Agarwal, Tongshuang Wu, Chris Donah... • 2026-03-25
The Stochastic Gap: A Markovian Framework for Pre-Deployment Reliability and Oversight-Cost Auditing in Agentic Artificial Intelligence
Biplab Pal, Santanu Bhattacharya • 2026-03-25
Retrieval Improvements Do Not Guarantee Better Answers: A Study of RAG for AI Policy QA
Saahil Mathur, Ryan David Rittner, Vedant Ajit Thakur, Daniel Stuart Schiff, ... • 2026-03-25
MARCH: Multi-Agent Reinforced Self-Check for LLM Hallucination
Zhuo Li, Yupeng Zhang, Pengyu Cheng, Jiajun Song, Mengyu Zhou, Hao Li, Shujie... • 2026-03-25
Raw Data (Debug)
{
"raw_xml": "<entry>\n <id>http://arxiv.org/abs/2602.19783v1</id>\n <title>Janus-Faced Technological Progress and the Arms Race in the Education of Humans and Chatbots</title>\n <updated>2026-02-23T12:38:42Z</updated>\n <link href='https://arxiv.org/abs/2602.19783v1' rel='alternate' type='text/html'/>\n <link href='https://arxiv.org/pdf/2602.19783v1' rel='related' title='pdf' type='application/pdf'/>\n <summary>We study the conditions under which technological advances, in combination with a lognormal wage distribution, incentivize agents into an inefficient educational arms race. Our model emphasizes that lognormal wage distributions imply that agents' wages increase exponentially in the level of their skill as well as in the level of technology. In turn, this exponential relation between skills, technology, and wages pressures agents into an exhausting race for the tails of the economy's skill distribution. Moreover, technological advances and overinvestment in education increase GDP and inequality, while welfare may decline. In an alternative interpretation, our model studies firms that invest in artificial intelligence of their chatbots and AI agents. For a wide range of specifications, firms, just like humans, have an incentive to choose corner solutions where investment is limited only by borrowing constraints.</summary>\n <category scheme='http://arxiv.org/schemas/atom' term='econ.GN'/>\n <published>2026-02-23T12:38:42Z</published>\n <arxiv:primary_category term='econ.GN'/>\n <author>\n <name>Wolfgang Kuhle</name>\n </author>\n </entry>"
}